现代电力2026，Vol.43Issue(3)：492-498,7.DOI:10.19725/j.cnki.1007-2322.2024.0070
基于改进人工蜂群算法的海上风电场柔直并网系统次同步振荡特性分析与抑制
Characterization and Suppression of Sub-synchronous Oscillations in Flexible Grid-connected Offshore Wind Farm Systems Equipped With SVGs Based Improved Artificial Bee Colony Algorithm
摘要
Abstract
The sub-synchronous oscillation(SSO)problem in offshore wind farms connected to grids through flexible DC systems occurs frequently.It is urgent to thoroughly understand the mechanism of offshore wind farm,flexible DC system,and SVG on SSO,and to develop effective sub-synchronous oscillation suppression methods.A small-signal model for a direct-drive wind turbine-based offshore wind farm equipped with SVG is constructed.Using the eigenvalue analysis method and the participation factor method,the system oscillation mode is investigated to identify the dominant state variables associated with SSO in offshore wind farms connected to the grid through flexible DC systems.The control parameters involved in the dominant state variables are optimized through the improved artificial bee colony algorithm(ABC)with chaotic mapping,aiming to further suppress the occurrence of SSO.The analysis results indicate that the offshore wind farm,the flexible DC system and the SVG jointly affect the oscillation mode of system SSO.Specifically,the offshore wind farm and the flexible DC system have different impacts on SSO under different oscillation modes,and the impact of the SVG on the SSO remains unaffected by changes in the oscillation mode.Further optimization of the controller parameters through the improvements to the ABC algorithm leads to an enhanced system eigenroot distribution and damping ratio,which effectively enhances the system stability.关键词
海上风电场/柔直输电/静止无功发生器/改进ABC算法/次同步振荡Key words
offshore wind farm/VSC-HVDC/SVG/improved ABC algorithm/SSO分类
信息技术与安全科学引用本文复制引用
魏书荣,冯启睿,何方,刘阳..基于改进人工蜂群算法的海上风电场柔直并网系统次同步振荡特性分析与抑制[J].现代电力,2026,43(3):492-498,7.基金项目
国家自然科学基金项目(52377063) （52377063）
上海市教委自然科学重大项目(2021-01-07-00-07-E00122) （2021-01-07-00-07-E00122）
上海高校特聘教授(东方学者)特聘教授(TP2020066) （东方学者）
上海科技创新行动计划(22DZ1206100).Project Supported by National Natural Science Foundation of China(NSFC)(52377063) （22DZ1206100）
Major Natural Science Project of Shanghai Municipal Education Commission(2021-01-07-00-07-E00122) （2021-01-07-00-07-E00122）
Distinguished Professor of Shanghai Universities(Oriental Scholar)(TP2020066) （Oriental Scholar）
Shanghai Science and Technology Innovation Action Plan(22DZ1206100). （22DZ1206100）
